Question 1

What is speech analytics?

Accepted Answer

Speech analytics is a technology that uses advanced natural language processing (NLP) to analyze spoken words in recorded phone conversations. Its primary goal is to obtain valuable information from spoken interactions and gain insights into customer behavior, agent performance, and overall contact center effectiveness.   This technology can make contact centers run more effectively and efficiently with data over time. It helps identify customer sentiments, detect customer satisfaction, and pinpoint specific topics or issues commonly raised by customers.

Question 2

What is the difference between speech analytics and voice analytics?

Accepted Answer

Speech analytics and voice analytics are related technologies used to analyze and extract insights from audio data, particularly in contact center and customer service environments. Speech analytics involves the analysis of spoken words and language within recorded audio interactions, such as phone calls or customer agent conversations. The primary goal of speech analytics is to extract valuable information from spoken conversations to gain insights into customer behavior, agent performance, and overall contact center effectiveness.   Voice analytics, on the other hand, is a broader concept that includes the analysis of various vocal elements and attributes in audio data, not just spoken language. In addition to speech content, voice analytics also examines other vocal characteristics like pitch, tone, and volume.

Question 3

How is Natural Language Processing (NLP) used in speech recognition?

Accepted Answer

Speech analytics systems use NLP to extract insights from recorded conversations or customer interactions. They can analyze text to detect patterns, identify customer sentiment, and understand customer preferences.   The system running speech analytics converts your spoken words into written text. NLP takes this written text and analyzes it to understand its meaning and extract valuable information.  This information can help improve services, identify issues, and provide better proactive support to customers, all without the need for cumbersome manual customer feedback forms.